1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
|
/*
* Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/core/CL/kernels/CLGaussianPyramidKernel.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
using namespace arm_compute;
CLGaussianPyramidHorKernel::CLGaussianPyramidHorKernel()
: _l2_load_offset(0)
{
}
BorderSize CLGaussianPyramidHorKernel::border_size() const
{
return BorderSize(0, 2);
}
void CLGaussianPyramidHorKernel::configure(const ICLTensor *input, ICLTensor *output)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U16);
ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) != output->info()->dimension(1));
for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
{
ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i));
}
_input = input;
_output = output;
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gaussian1x5_sub_x"));
// Configure kernel window
constexpr unsigned int num_elems_processed_per_iteration = 16;
constexpr unsigned int num_elems_read_per_iteration = 20;
constexpr unsigned int num_elems_written_per_iteration = 8;
const float scale_x = static_cast<float>(output->info()->dimension(0)) / input->info()->dimension(0);
Window win = calculate_max_window_horizontal(*input->info(), Steps(num_elems_processed_per_iteration));
AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration, scale_x);
// Sub sampling selects odd pixels (1, 3, 5, ...) for images with even
// width and even pixels (0, 2, 4, ...) for images with odd width. (Whether
// a pixel is even or odd is determined based on the tensor shape not the
// valid region!)
// Thus the offset from which the first pixel (L2) for the convolution is
// loaded depends on the anchor and shape of the valid region.
// In the case of an even shape (= even image width) we need to load L2
// from -2 if the anchor is odd and from -1 if the anchor is even. That
// makes sure that L2 is always loaded from an odd pixel.
// On the other hand, for an odd shape (= odd image width) we need to load
// L2 from -1 if the anchor is odd and from -2 if the anchor is even to
// achieve the opposite effect.
// The condition can be simplified to checking whether anchor + shape is
// odd (-2) or even (-1) as only adding an odd and an even number will have
// an odd result.
_l2_load_offset = -border_size().left;
if((_input->info()->valid_region().anchor[0] + _input->info()->valid_region().shape[0]) % 2 == 0)
{
_l2_load_offset += 1;
}
update_window_and_padding(win,
AccessWindowHorizontal(input->info(), _l2_load_offset, num_elems_read_per_iteration),
output_access);
output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
ICLKernel::configure_internal(win);
}
void CLGaussianPyramidHorKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
Window win_in(window);
win_in.shift(Window::DimX, _l2_load_offset);
//The output is half the width of the input:
Window win_out(window);
win_out.scale(Window::DimX, 0.5f);
Window slice_in = win_in.first_slice_window_2D();
Window slice_out = win_out.first_slice_window_2D();
do
{
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input, slice_in);
add_2D_tensor_argument(idx, _output, slice_out);
enqueue(queue, *this, slice_out);
}
while(win_in.slide_window_slice_2D(slice_in) && win_out.slide_window_slice_2D(slice_out));
}
CLGaussianPyramidVertKernel::CLGaussianPyramidVertKernel()
: _t2_load_offset(0)
{
}
BorderSize CLGaussianPyramidVertKernel::border_size() const
{
return BorderSize(2, 0);
}
void CLGaussianPyramidVertKernel::configure(const ICLTensor *input, ICLTensor *output)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U16);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != output->info()->dimension(0));
for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
{
ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i));
}
_input = input;
_output = output;
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gaussian5x1_sub_y"));
// Configure kernel window
constexpr unsigned int num_elems_processed_per_iteration = 8;
constexpr unsigned int num_rows_processed_per_iteration = 2;
constexpr unsigned int num_elems_written_per_iteration = 8;
constexpr unsigned int num_elems_read_per_iteration = 8;
constexpr unsigned int num_rows_per_iteration = 5;
const float scale_y = static_cast<float>(output->info()->dimension(1)) / input->info()->dimension(1);
Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration, num_rows_processed_per_iteration));
AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_written_per_iteration, num_rows_per_iteration, 1.f, scale_y);
// Determine whether we need to load even or odd rows. See above for a
// detailed explanation.
_t2_load_offset = -border_size().top;
if((_input->info()->valid_region().anchor[1] + _input->info()->valid_region().shape[1]) % 2 == 0)
{
_t2_load_offset += 1;
}
update_window_and_padding(win,
AccessWindowRectangle(input->info(), 0, _t2_load_offset, num_elems_read_per_iteration, num_rows_per_iteration),
output_access);
output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
ICLKernel::configure_internal(win);
}
void CLGaussianPyramidVertKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
ARM_COMPUTE_ERROR_ON(window.x().step() != 8);
ARM_COMPUTE_ERROR_ON(window.y().step() % 2);
Window win_in(window);
win_in.shift(Window::DimY, _t2_load_offset);
Window win_out(window);
win_out.scale(Window::DimY, 0.5f);
Window slice_in = win_in.first_slice_window_2D();
Window slice_out = win_out.first_slice_window_2D();
do
{
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input, slice_in);
add_2D_tensor_argument(idx, _output, slice_out);
enqueue(queue, *this, slice_out);
}
while(win_in.slide_window_slice_2D(slice_in) && win_out.slide_window_slice_2D(slice_out));
}
|
